what is inspired-mino-design-skills fr?

This repository is an unofficial collection of AI Skills built around software design principles, inspired by publicly published material from a Japanese engineer known as mino-driven. The project makes clear it has not been reviewed, endorsed, or approved by that person or their organization. The goal is not to copy anyone's writing style or conclusions, but to turn design principles into repeatable checks: confirming the problem, purpose, context, requirements, contracts, models, quality goals, and public boundaries of a piece of software so that decisions are backed by evidence rather than guesswork. The project is currently marked experimental and in preview, at version 0.9.0. Its own status notes describe mixed results: structural checks pass on Linux and on PowerShell running through WSL, but fail on a native macOS test runner due to a specific script issue. The maintainers are explicit that this is not yet a stable release. A stable, behavior-verified release would require an authorized reviewer to repeatedly run frozen test cases against independent checks and confirm they pass across every required platform. Final decisions about product value, quality tradeoffs, and whether to release are reserved for humans, not the AI. The repository is organized as a set of Skills meant to be used at different points in a software project. One helps frame a problem and its goals before coding starts. Others check whether a domain model is missing important concepts, states, or failure cases, turn requirements into testable contracts, separate what users see from how something is implemented internally, guide system-wide architecture decisions, or tie several of these design steps together for medium to large changes. A shared core Skill provides common functionality that the others rely on, but it is not meant to be used directly by developers. The suite targets Windows, Linux, macOS, and WSL, and accounts for platform-specific differences like file paths, permissions, and shells while keeping the underlying design reasoning the same across all of them. It is intended for AI coding assistants and developers who want a structured, checkable approach to software design decisions rather than a quick script or code snippet.